Technological and Operational Scenarios on Aircraft Fleet-Level towards ATAG and IATA 2050 Emission Targets
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
AIAA 2017-3771
AIAA AVIATION Forum
5-9 June 2017, Denver, Colorado
17th AIAA Aviation Technology, Integration, and Operations Conference
Technological and Operational Scenarios on Aircraft Fleet-
Level towards ATAG and IATA 2050 Emission Targets
Ploetner, Kay Olaf*; Rothfeld Raoul†; Urban, Marcia‡; Hornung, Mirko§
Bauhaus Luftfahrt e.V., Willy-Messerschmitt-Straße 1, Taufkirchen, 82024, Germany
Tay, Gilbert**
Institute of Aircraft Design, Department of Mechanical Engineering, Technical University Munich,
Boltzmannstrasse 15, Garching, 85748, Germany
Oguntona, Oluwaferanmi††
Munich Aerospace e.V., Faculty of Aerospace Engineering, Willy-Messerschmitt-Str. 1, Taufkirchen, 82024,
Germany
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
In the face of global climate change various private and public stakeholders of the commercial
aviation industry have proclaimed ambitious goals aimed at reducing the global fuel consumption
and thus mitigating the future environmental impact of aviation by halving aviation´s fleet-level
emissions by 50 % compared to year 2005. Here, the potential of aircraft technologies, production
ramp-ups and operational improvement options are assessed to quantify the global fleet-level
emissions up to the year 2050. Based on the estimation of impact of next-generation aircraft types
with market entries until 2020, fifteen fleet-level emission scenarios based on various technology,
production and operational scenarios with their single contribution towards long-term emission
goal, are the objectives of this paper. A numerical model of the global air transport fleet is employed
to quantify the fleet-wide fuel demand and carbon-emissions reduction impact and conduct
sensitivity analyses. New aircraft technologies together with up to radical ramp-up timelines might
lower fleet-level fuel burn until year 2050 between -17 % to -27 %. Increasing aircraft productivity
by increasing loadfactors, installed seats and increased aircraft utilisation further reduce fleet-level
fuel burn until year 2050 by -7 % to -8 %. The application of retrofit solutions for in-fleet aircraft
can reduce the fleet-level fuel burn until year 2050 by around -3 %. Halving regional RPK growth
rates might lead to fleet-level fuel burn reductions by around -6% until year 2050. The results
obtained clearly indicate that the climate goals cannot be reached solely by following long-term
research goals for aircraft technology improvements, because of slowing effects on fleet level. Even
following the long-term research goals for aircraft technology improvements combined with radical
production ramp-ups and significant improvements in aircraft productivities will lead to a carbon-
neutral growth until year 2050 but at roughly 10% higher emission compared to the IATA goals
until year 2035.
I. Long-term goals for aviation
Over the last 100 years, aviation transformed from an elite mode of transport for niche markets to a mass
transportation system serving long-haul as well as medium and short-haul markets worldwide. The aviation industry
has grown strongly over the past decades at a global rate of around 5 % per year 1 and above, measured in transport
capacity (revenue passenger kilometres, RPK). Forecasts for market developments issued by all main aviation
stakeholders2-12 predict further growth in transport capacity by 4 to 5 % annually until 2030 at global average - roughly
*Head Economics & Transportation, kay.ploetner@bauhaus-luftfahrt.net
† Research Assistants Economics & Transportation, raoul.rothfeld@bauhaus-luftfahrt.net
‡ Research Assistants Economics & Transportation, marcia.urban@bauhaus-luftfahrt.net
§ Director Research and Technology, mirko.hornung@bauhaus-luftfahrt.net
** Research Assistant, gilbert.tay@tum.de
†† Scholarship Recipient, oluwaferanmi.oguntona@bauhaus-luftfahrt.net
1
American Institute of Aeronautics and Astronautics
Copyright © 2017 by Dr. Kay Olaf Ploetner, Bauhaus Luftfahrt, Willy-Messerschitt-Strasse 1, 82024 Taufkirchen, Germany. Published by the American Institute of Aeronautics and Astronautics, Inc., with permissiontranslating into doubling of transport capacity by 2030 compared to today. Particularly high growth rates, partly
surpassing 6 % per year, are expected for emerging countries, for example in the Asia-Pacific region, driven by the
transition to middle- or even high-income countries with a growing middle class and the associated changes in travel
behaviour13. Within the context of this rapid growth, environmental awareness of societies and general actions to
mitigate global climate change have led various institutions and stakeholders to formulate and proclaim aspirational,
partially non-binding quantitative goals for limiting greenhouse gas emissions (GHG) of the future global air transport
fleet. Among these institutions are the International Civil Aviation Organization (ICAO) 14, the International Air
Transport Association (IATA)15, the Air Transport Action Group (ATAG)16 and the European Union (EU)17. The most
prominent and frequently cited targets addressing the emission quantities of carbon dioxide (CO 2) at global aircraft
fleet level have been published by IATA and ATAG and comprise three major items:
(1) Fleet-wide efficiency improvement of 1.5 % annually from the present until 2020
(2) Cap of CO2 emissions from 2020 onwards (“carbon-neutral growth”) enabled by market-based measures
(3) Halving of the global fleet’s overall CO2 emission quantities by 2050 relative to 2005 levels
At aircraft level, the EU envisages in its long-term research agenda17, a reduction of CO2 emissions by 75 %
compared to typical aircraft in service in the reference year 2000. The EU targets are considered as being on an equal
footing with those announced by ICAO14, IATA15, and the U.S. National Aeronautics and Space Administration
(NASA)18, levelling the long-term research goals for aircraft technologies. Technology goals for CO 2 emissions, as
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
originally defined in Vision 202019 and AGAPE 202020, were categorised into airframe, propulsion and other areas
like air traffic management (ATM) and airline operations. Up to the year 2035, a 60 % reduction in fuel burn and CO 2
emissions per RPK is to be achieved, and a 75 % reduction in CO2 emissions is set as a target for the year 2050,
relative to technology standards of the reference year 2000.
A. Short-to-medium term developments in aviation
Besides these long-term research goals to reduce the ecological footprint at aircraft level, aircraft manufacturers
are continuously updating their current product portfolio with completely new aircraft programmes and performance
improvement packages for existing product lines. Over the last 10 to 15 years, a strong focus, and hence competition,
was set on new long-haul aircraft programmes like Airbus A380, Boeing 787, Boeing 747-8, and Airbus A350, which
entered the markets in 2005, 2011, 2012 and 2014, respectively. A block fuel reduction of the Boeing 787 compared
to its predecessor – the Boeing 767 – of around 20 % was achieved21. For the Airbus A350, a 25 % block fuel reduction
compared to the current Boeing 777 family is claimed 22. Besides new aircraft programmes, both Airbus and Boeing
will also improve their existing A330 and 777 programmes by more efficient wing designs and incorporating latest
available engine technologies, resulting in the Airbus A330neo (new engine option) and Boeing 777-X family (incl.
777-8/9), achieving block fuel reductions between 13% and 20 %.
YEAR
2008 (initial fleet) 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
C1: Long-range combi (TA)
Boeing MD11
C2: Long-range heavy (TA) Next Generation C2 (BADA)
Boeing 747-400 Boeing 747-8
C3: Mid-range freighter (n/a)
Boeing 767-300F
C4:Jet commuter (SA) Next Generation C4 -16%
Embraer E190 Bombardier C-Series Embraer E-Jet E2
Mitsubishi Regional Jet
C5: Long-range freighter (n/a) Next Generation C5 -16%
Boeing 747-400F Boeing 747-8F
C6: Turboprop commuter (SA)
ATR 72-500
C7: Mid-range (TA) Next Generation C7 (BADA)
Boeing 767-300 Boeing 787 Airbus A330NEO
C8: Long-range (TA) Next Generation C8 -18%
Boeing 777-200 Airbus A350XWB Boeing 777-X
C9: Short-medium range (SA) Next Generation C9 -15%
Airbus A320 Airbus A320NEO Boeing B737MAX
Irkut MC-21
Comac C919
Figure 1: Next-generation aircraft types and associated gains in fuel efficiency23 launched until 2017
2
American Institute of Aeronautics and AstronauticsFor the short-haul markets, the availability of the Geared Turbofan engine technology, offering promising fuel
burn reductions of around 15 %24, led to several launches of new programmes like Bombardier’s CSeries or existing
aircraft programmes like Airbus’ A320 and Boeing’s 737 families being updated with this latest engine technology.
However, despite these substantial efforts to develop new or upgraded aircraft programmes in order to increase
fuel efficiency, it is obvious that the target of carbon-neutral growth from 2020 onwards will not be met. Today, more
than 14,000 single-aisle aircraft are operating, and a growth to over 30,000 aircraft within the next 20 years is
expected25. Even at current highest production rates of around 120 aircraft per month for Airbus A320 and Boeing
737 single-aisle aircraft families, the rate of market penetration of new and more efficient aircraft is slowing down the
achievement of overall ambitious emission reduction targets on fleet level.
II. Review of Aviation Fleet-Level Emission Scenarios
Several studies have investigated scenarios of future fleet-level emissions at different geographical scales, time
horizons, considering fuel life-cycle emissions and/or full-flight emissions.
Dray et al.26 investigated the effect of global emissions trading on global aviation demand and emissions using the
Aviation Integrated Model (AIM). Three scenarios were used, combined differently with five stringency levels of
atmospheric CO2 stabilization, each with an associated carbon price. Main differences in the scenarios are in global
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
distribution of GDP per capita growth and in oil and carbon prices, with carbon prices directly affected by the level
of stringency simulated. Main fuel reduction options are the open rotor technology assumed to enter the fleet in 2020
and biomass-derived synthetic jet fuel, in a 20% blend with Jet A, also assumed to be available from 2020. Other
mitigation options were incorporated, like winglets as aircraft retrofit option which has a low effect on global
emissions. Also, air traffic management (ATM) improvement was assumed to be non-optional, resulting in a 4%
decrease in total global fuel burn. Furthermore, engine upgrade kits were assumed to have low adoption rates.
By 2050, their result reveals that aviation-related CO2 emissions may range from double the 2005 level (under the
most stringent atmospheric CO2 stabilization target of 450 ppm) to five times the 2005 levels (when no emissions
trading took place). The authors found out that the adoption of new technologies in response to increased carbon costs
resulted in approximately two-third of the total emissions reductions while the last third was a result of demand
reduction. The open rotor as a new technology option was particularly incorporated into the fleet in scenarios with
high oil prices in order to save total fuel and carbon costs. On the other hand, biofuels, assumed to be priced at similar
prices or higher than Jet A, were incorporated into the fleet in high stringency scenarios. The functionality of the
emissions trading scheme is such that the expected increase in aviation CO2 will be offset by reductions in emissions
from other sectors.
Owen et al.27 developed aviation emission scenarios to 2050 that were designed to interpret the IPCC storylines
under four main families A1B, A2, B1 and B2 with a further outlook to 2100. Additionally, a scenario was developed
assuming the ambitious technology targets of ACARE would be achieved. Scenarios were defined assuming that
political and societal factors affect future travel both globally and with different regional impacts. Aircraft added to
the fleet after the base year (e.g. B787, A380) in order to replace retired older aircraft were estimated with about 20%
fuel efficiency such that a fleet-wide efficiency improvement of approximately 1% year -1 from 2000 up to 2020 was
estimated. Beyond 2020, ACARE technology goals and ICAO’s Committee on Aviation Environmental Protection
(ICAO/CAEP) long term technology goals (LTTG) were used in the scenarios.
Their work was implemented using the Future Aviation Scenario Tool (FAST model). This global model of aircraft
movements and emissions has a baseline year of 2000 and combines a global aircraft movement’s database of
scheduled and non-scheduled air traffic with data on fuel flow provided by a separate commercial aircraft performance
tool PIANO. They normalized the CO2 emissions in the base year to the IEA total aviation fuel sales figure of 214
Mt/year, to account for previous differences in the emissions estimate due to assumption of great circle distances and
the difficulty in estimating military emissions. Until the year 2020, traffic growth rate projection of ICAO/CAEP
(4.3% annual average) was used; whereas, traffic demand for each scenario was calculated using global GDP growth
as the main driver, in addition to relative maturity of aviation demand in the regions. Their result shows that aviation
emissions grow from 2000 to 2050 by a factor of one and a half (with fuel efficiency improvement of 2.1% per year
between 2020 and 2050) and three and a half (with fuel efficiency improvement of 1% per year between 2020 and
2050)27.
ICAO’s CAEP assessed the present and longer-term impact and trends of aircraft noise and engine emissions
starting from a base year of 2005 till a target year of 2050 28. Their study was conducted using United States Federal
Aviation Administration’s (FAA) Aviation Environmental Design Tool (AEDT), EUROCONTROL’s IMPACT and
the FAST model. Measures considered to reduce fuel burn include contribution of aircraft technology, improved ATM,
and operational improvements resulting from better infrastructure use. The analysis was centered on emissions from
3
American Institute of Aeronautics and Astronauticsinternational aviation. Given that international and domestic aviation represented 65% and 35% of global aviation
traffic in 2010, with projected values of 70% and 30% for 2050 28, values of global aviation emissions in 2005 and
2050 were calculated using their results, with the 2005 values extrapolated based on this information.
An RPK annual growth rate of 4.9% between 2010 and 2030 was assumed, with nine scenarios of fuel efficiency
improvements developed to simulate the contribution of aircraft technology improvement to emissions reduction. An
aircraft fuel efficiency improvement scenario of 1.4% together with ATM and operational improvements resulted in
1039 Mt more CO2 emission above the net emissions values estimated for 2020. Thus, in order to achieve the carbon
neutral growth target as from 2020, the contribution of alternative jet fuels (AJF) from feasible stocks (starchy crops,
sugary crops, lignocellulosic crops, oily crops, agricultural residues, forestry residues, waste fats, oils and greases,
microalgae, and municipal solid waste) to fuel replacement and GHG trends was investigated. The most effective
scenario assumed production ramp ups for AJF in 2050 to completely replace petroleum-derived jet fuel. This scenario
resulted in global aviation emission in 2050 growing by a factor of less than one and a half compared to the estimates
for 2005.
Hassan et al.29 proposed a framework to assess the performance of the future NAS under different scenarios that
consider varying technology, operation, and biofuel contributions to mitigate the environmental impacts of aviation.
Vehicle performance was determined for different combinations of airframes, engines, and technology packages.
Seven vehicle classes of tube and wing aircraft configurations with Geared Turbo fan engine were considered, namely
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
turboprop, regional jet, small single aisle, large single aisle, small twin aisle, large twin aisle and very large aircraft,
simulating only domestic operations in the United States. Technology improvements were modeled as continuous
improvements in fuel efficiency and thus reduced CO 2 emissions. The best improvement at aircraft level, the N+3
technology, was to achieve an aircraft fuel consumption reduction of 60% referenced to the B737-800 with CFM56-
7B engines. Scenarios were based on their best estimates of available technology sets within the simulation timeframe
without use of biofuels and operational measures. Their study results showed, however, that the carbon-neutral growth
goal could be reached using technology improvements, claiming that the goal of reducing CO2 emissions in 2050
relative to 2005 values could not be reached by technologies alone. They suggested that operational measures and
more biofuels would be needed to fill the remaining gap.
Schilling et al.30 reported of a study conducted by the German Aerospace Center (DLR) in cooperation with the
International Air Transport Association (IATA) to investigate the benefits, challenges and resulting CO2 emissions
reduction potential at fleet level of three kinds of novel aircraft configurations- a fully-electric aircraft concept, a strut-
braced wing with open rotor configuration and a blended wing body configuration; and two sustainable fuel
technologies- a sun-to-liquid drop-in fuel, and a liquid non-drop-in fuel. The DLR fleet and fuel forecast tool FFWD31
was used in forecasting the potential impact of each configuration as well as a combination of the three configurations
and excluding potential economically-driven delays such as poor world economics or reluctance to invest in large
high-risk projects. The block fuel burn saving potential results bases on assumptions of 100% for universally-electric
aircraft assumed to have entry into service (EIS) between 2030 – 2035, 50% for blended wing body aircraft assumed
to have EIS at the earliest in 2040, and 29% up to 62% for strut-braced wing with open-rotor having EIS years 2030
and 2045 respectively. Furthermore, an underlying RPK annual growth scenario of 2.0% from 2005-2010, 5.3% from
2010-2020, 4.5% from 2020-2030, 4.0% from 2030-2040, and 3.7% from 2040-2050 was used29. By 2050, the result
reveals that aviation-related CO2 emissions may range from three and a half times (under the baseline scenario) to
four and a half times the 2005 levels (with three aircraft configurations considered).
Table 1 (overleaf) summarizes the different studies reviewed, the measures of their baseline and strictest scenarios
and the respective resulting factors of increase or decrease in the fleet CO2 emissions, with estimates given where
available. Although these studies involve extensive assumptions on different combinations of future aircraft
technologies, alternative fuels, fuel efficiency improvements and operational measures, none of them evaluated these
measures in combination with production ramp-up or aircraft productivity measures.
Therefore, all studies showed that available aircraft technology improvements are outpaced by the strong growth
in aviation today. The reviewed studies revealed an increase in global emission of a factor of up to 6 for the baseline
scenarios in 2005. Assuming future novel and more radical technologies on aircraft level and alternative fuel paths,
the studies concluded that global emissions growth can be limited to a factor of 1.5 to 3.5 compared to the 2005
baseline. Only the study of Hassan et al. 201529 calculated a reduction of aviation´s emissions in the US to a factor of
0.9 compared to 2006 baseline only enabled by large usage of alternative fuels. Most of the studies do not take into
account that future novel and more radical technologies with large CO2 emission reduction potentials are still at very
low technology readiness levels and hence far from industrial implementation leading to large challenges to the
aviation industry in terms of technology maturation, design and development as well as production. Even in the case
of a rapid technology maturation, a fleet-wide penetration would require radical production ramp-ups and an
4
American Institute of Aeronautics and Astronauticsaggressive industrialisation strategy for such novel technologies. Therefore, in the following chapter, four different
scenarios were defined to quantify the impact of novel technologies, operational improvements, aircraft ramp-up and
production scenarios as well as future RPK growth rates.
Table 1. Summary of considered technological and operational cases: Baseline and Strictest Scenario
Assumptions and CO2 Emissions Results from Studies Reviewed
Baseline Scenario Strictest Scenario
Base year - CO2 emissions CO2 emissions
Target Year in target year in target year
(Geographic as factor of as factor of
Study al scope, Description base year Scenario Description base year
CO2 values values
estimation (estimates, if (estimates, if
type) available) available)
MIT’s IGSM scenario of high oil
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
prices and high rates of economic
2005 – 2050 growth in US, western Europe, and
MIT's IGSM
(Global, fuel low levels of economic growth in the
Dray et scenario, with no
life-cycle 4.8 (3000 Mt) developing world, high carbon prices 2.0 (1200 Mt)
al. 201026 emissions trading
CO2 at high stringency levels (450ppm) of
scheme
emissions) carbon trading. Aircraft technology
available in final simulated year are
open rotor engine aircraft and biofuel
Aircraft technology available in final
2000 – 2050 Fuel Efficiency simulated year complying with
Owens et (Global, full- grows at 1% per ACARE targets: aircraft fuel
3.5 (2418 Mt) 1.5 (1025 Mt)
al. 201027 flight CO2 year from 2000 to efficiency [kg/seat km offered]
emissions) 2050 reduction of 83% compared to base
year. Demand growth is slower
Fuel efficiency grows at 1.4% per
2005 – 2050 Fleet renewal. No
year. Improved ATM and
ICAO (Global, full- technology and 6.0
infrastructure use, petroleum-based jet 1.4 (940 Mt)
201628 flight CO2 operational (3750 Mt)
fuel completely replaced by alternative
emissions) improvement
jet fuel
Aircraft technology available in final
2006 – 2050 simulated year complying with
Hassan Business as usual,
(USA, full- CLEEN, ERA and FW program
et al. no new technology 1.9 0.9
flight CO2 targets of aircraft fuel consumption
201529 introduced
emissions) reduction of 60% compared to B737-
800 with CFM 56-7B engines
Global aircraft fleet
and fuel
2005-2050 consumption
Schilling
(Global, full- development Electric Aircraft + Strut-braced wing +
et al. 4.5 3.5
flight CO2 considering only Blended wing body
201630
emissions) evolutionary
technologies as
detailed by IATA31
5
American Institute of Aeronautics and AstronauticsIII. Technological and Operational Scenarios on Aircraft Fleet-Level
To be able to quantify the effectiveness of various technological and operational improvement on global emissions
in 2050 as well as cumulative global emissions up to the year 2050, scenarios were defined taking aircraft technologies
and configurations, aircraft production ramp-ups, aircraft productivities, RPK growth changes and retrofit options
similar to Dray et al.26 into account.
For aircraft technologies and configurations, three cases were setup taking fuel reductions on aircraft level into
account. In the first case (1.1), it is assumed that the aviation industry can develop and deliver new aircraft following
the SRIA goals of -43% fuel burn reduction of all new aircraft with EIS between 2020 and 2035, -60% fuel burn with
EIS between 2035 and 2050. In Case 1.2, only a -22% fuel burn reduction (~50% shortfall due to no new A/C
programs) for aircraft between 2020 and 2035 are assumed taking into account that most of the current aircraft
programs will be upgraded by re-engined, re-winged options32. Between 2035 and 2050, it is assumed that aviation
industry can deliver a 60% fuel reduction for all aircraft programs. In Case 1.3, shortfalls in block fuel reductions on
aircraft level until 2050 are assumed incorporating block fuel results for future short and long-haul conventional
aircraft up to year 205033 without any radical new aircraft technologies like hybrid-propulsion or novel airframe
morphologies.
Possible effects of new aircraft technologies on their market penetration are captured by three different aircraft
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
production ramp-up cases. For this study, production rates and production increases of current aircraft programs
following an analysis of Leeham34 until year 2020 were used, after 2020 it is assumed that aircraft production increases
with RPK growth. In Case 2.1, it is also assumed that new aircraft programs will follow current ramp-up timelines as
seen for the B787 or A350XWB of six years35 from first delivery to full-production. In Case 2.2, all new aircraft
programs will face more ambitious ramp-up timelines resulting in timelines of 3 years until full production. In Case
2.3 all new aircraft programs will have a radical ramp-up timeline of one year to full production.
Besides the aircraft technologies and production capabilities, also possible emission reduction options on an
operational level like aircraft productivity were analysed. In Case 3.1, the average loadfactor is increase to 95% (from
80.4% in 201536) in three different timelines (see also scenario descriptions). In Case 3.2, the average number of
installed seats is increased by 10% for all aircraft programs taking additional fuel burn into account. In Case 3.3, the
average aircraft utilization (measured by number of flights per years) is increased by 10%.
In Case 4, regional RPK growth rates inside EU, North America and Asia are halved from 2017 until 2050 using
initial growth rates provided by Boeing25 until year 2035 with the assumption of unchanged growth rates until year
2050. In Case 5, fuel reduction retrofit solutions with a 4% block fuel reduction for in-fleet aircraft are modelled. A
full market penetration of all in-service aircraft is assumed within eight years following conventional heavy
maintenance timeframes.
Table 1. Summary of considered technological and operational cases
Category Input for Fleet Simulation Framework
Case 1.1: -43% fuel burn of all new aircraft with EIS between 2020 and 2035, -60% fuel burn
of all new aircraft with EIS between 2035 and 2050
Case 1.2: -22% (~50% shortfall due to no new A/C programs) fuel burn of re-engined, re-
Aircraft technologies & winged A/C between 2020 and 2035, -60% fuel burn of all new aircraft with EIS between
configurations 2035 and 2050
Case 1.3: -22% (~50% shortfall due to no new A/C programs) fuel burn of re-engined, re-
winged A/C between 2020 and 2035, -48% (~20% shortfall) fuel burn of all new aircraft with
EIS between 2035 and 2050
Case 2.1: New aircraft programs with current ramp-up timelines of six years (status quo)
Aircraft production ramp-up
Case 2.2: New aircraft programs with ambitious ramp-up timelines within three years
Case 2.3: New aircraft programs with radical ramp-up timelines of one year to full production
Case 3.1: Increase of average load factor to 95%
Aircraft productivity
Case 3.2: Increase of average number of installed seats by 10%
Case 3.3: Increase of average aircraft utilization by 10%
Case 4: Reduction of regional RPK growth rates (e.g. inside EU, North America and Asia) of
Change of RPK growth rates
50%
Fuel reduction retrofit Case 5: Application of retrofit solution for in-fleet aircraft from 2008 until last retired A/C from
solutions for in-fleet aircraft initial fleet
6
American Institute of Aeronautics and AstronauticsIV. Air transport fleet modelling
Given the goals of this paper, a simplistic comparison of the performance of current and next-generation aircraft
types at a single-mission level is insufficient. Instead, fleet-wide effects resulting from the phase in and
decommissioning processes of aircraft types that enter the global fleet at a certain moment in the future have to be
taken into account. Once a new type has reached technological maturity for commercial operations with an airline, it
will not simply replace all of the corresponding older types at once but gradually replace these aircraft and, in this
way, replenish the airline’s fleet. In order to capture the integration and penetration effects of the next-generation
aircraft and technologies, the “Fleet System Dynamics Model (FSDM)” has been developed and further extended37,38,
39
. The fundamental functioning of this model has been derived from the “macro” or “top-down” approach to fleet
planning that is based on a relatively high-level aggregated analysis39,40. The FSDM translates air traffic market data
(e.g., growth rates in different regional markets, payload factors, and aircraft production rates) into quantitative data
that addresses the future fleet size, composition, and age distribution. This is achieved through the simulation of the
global aircraft commissioning, operations, and retirement procedures for distinct world regions and at a global level
as a function of time.
A. FSDM: Overview
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
The FSDM is divided into two model components: the air transport fleet model and the air transport network model.
The former dynamically determines the size and structure of the global fleet of commercial transport aircraft on a
year-by-year basis. The time-step used in the model is hence one year. The latter defines the air routes that interconnect
intra- and intercontinental air traffic markets with each other to form and represent the global network of air transport
routes on which the air transport fleet operates. The macro approach to fleet planning underlying the FSDM has two
decisive consequences for the basic functioning of the model: (1) For each year of simulation, the model requires a
target amount of ASKs and ATKs, or alternatively, a target amount of RPKs and RTKs along with load factor data,
in order to determine the “capacity gap,” which in turn stipulates the amount of new aircraft units to be added to the
fleet. For each year of simulation, the model hence determines the fleet that is required to deliver a certain transport
performance. (2) The user must initialize the model by defining a start year of simulation along with an initial fleet of
aircraft (including a definition of the fleet size, composition, and age distribution) as well as the initial transport supply
that this fleet must deliver. To capture the dynamic evolution of the global air transport fleet, the FSDM uses the
principles of System Dynamics41. In particular, interdependent stocks and flows are utilized to capture the dynamics
of the fleet evolution as a function of time. The fleet (stock) is essentially determined by two flows, the ‘Aircraft
introduction’-inflow and the ‘Retire aircraft’-outflow. The ‘Aircraft introduction’-inflow is aimed at delivering new
aircraft to the fleet, depending on the growth rates of air traffic defined by the user. In addition, it is constrained by
both the availability of aircraft (in terms of whether or not a particular type of aircraft is being produced in a specific
year of simulation) and the capability of the aircraft manufacturers to deliver the amount of aircraft units required.
The ‘Retire aircraft’-outflow is determined by an FESG-based aircraft retirement model42 that is a part of the FSDM
using aircraft-specific survival curves. Given an initial age distribution of the fleet, the model will apply predefined
survival curves to the various types of aircraft simulated by the model to statistically determine the amount of aircraft
to be retired in each year of simulation.
B. Model assumptions and limitations
This section presents the various underlying model assumptions and limitations employed in the FSDM. Randt46
similarly employed most of these in his work. Some assumptions however, have been further developed here to
increase model fidelity.
1. Airline competition: Commercial aviation is an industry sector that is strongly characterized by competition among
airlines courting passengers at a local, regional, and global level. However, the modelling of airline competition
requires profound economic understanding and modelling capability that was not available during the work of this
paper. As a result, similar to the work of Tetzloff and Crossley34, the model simulates “one benevolent, monopolistic
airline” that exists to meet all transport demand worldwide.
2. Fleet allocation: Usually, airlines will assign their fleets to a route network in a way to maximize profit. Profit
maximization is then used as the objective function required for solving the “Fleet Assignment Problem (FAP)” 44.
The simulation of the model in the absence of airline competition uses a fuel burn optimization function instead of
profit maximization. Hence, the FSDM assigns aircraft to the route network in order to minimize the total fleet fuel
consumption. This ensures consistency with the other model assumptions and at the same time enables the simulation
and development of a fuel-optimal fleet.
7
American Institute of Aeronautics and Astronautics3. Representation of the global air transport fleet: Almost 200 different types of aircraft were part of the global air
transport fleet that contributed to the total transport supply in 200813. Including all types would lead to a very high
degree of complexity of the FSDM. Therefore, to keep complexity within manageable limits, the model defines nine
distinct aircraft categories to represent the global fleet in 2008. New aircraft programmes up to the year 2050 can be
added indefinitely as separate aircraft categories.
4. Representation of the global route network: More than 37,000 different O-D pairs formed the global network of air
routes in 200845. Again, representing the entire set of O-D pairs in the FSDM would lead to a significant degree of
complexity of the model that would make its handling very difficult. Therefore, the FSDM fundamentally defines six
global regions (Africa, Asia, Europe, Latin America, North America, and the Middle East) that together form twenty-
one intra- and interregional connections referred to as ‘routes’46. These routes establish the simulated global air
transport network. Three distinct stage lengths and their route specific distribution are furthermore employed to
characterize each route. To initialize the FSDM, statistical analyses of the OAG database were conducted to supply a
definition of the aircraft categories and route-specific stage lengths. During the simulation of the subsequent years,
the stage lengths are considered to be constant over time.
5. Further model limitations: In its current version46, the FSDM features four additional methodological limitations
that decrease the model accuracy. (1) First the user has to define the utilization characteristics of each aircraft category.
(2) The FSDM always retires aircraft on a statistical basis, regardless of the current situation of aircraft demand. (3)
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
The FSDM does not support the modelling of temporary aircraft storage that airlines undertake in reality during short
periods of economic decline in order to adapt their transport capacities accordingly. On the one hand, integrating the
above capabilities into the FSDM would certainly increase the overall model accuracy (and equally raise the model
complexity by the same degree). On the other hand, a validation of the current version of the model (not presented in
this paper) revealed that even without these capabilities, the FSDM is very well capable of determining a realistic
development of the global air transport fleet.
C. User input data required
The FSDM requires a range of input data that have to be supplied by the user in order to enable the proper
functioning of the model46. The target year of simulation stipulates the final year of the fleet simulation. Current
aircraft production capacities define the number of aircraft with which the types of the initial fleet are produced. Next-
generation aircraft data define which types of aircraft will enter the fleet in the future. The user must provide the full
range of aircraft data including performance and utilization data, and survival curves. Next-generation aircraft
production capacities define the number of aircraft with which the future types are produced. Regional market growth
factors define the year-on-year change of the RPKs and RTKs in each one of the 21 route groups between 2008 and
the target year of simulation46.
D. Aircraft performance modelling
Aircraft performance modelling is a core capability of the FSDM. The performance modelling tool employed in
the FSDM utilises the aircraft performance model (APM) that is fundamentally based on the Base of Aircraft Data
(BADA) that has been created and is now being maintained and distributed by Eurocontrol 37. Over the last years,
BADA has become a widely utilized and recognized APM in the international scientific community. Today, it can
certainly be considered as a standard tool for performance simulation purposes of civil aircraft. Response surfaces of
the BADA APM have been used in the FSDM to primarily determine the fleet-wide fuel consumption and CO2
emission quantities. The model can also calculate further emission substances like NO x, CO, and unburned
hydrocarbons, provided that adequate data is available (e.g., supplied by the ICAO Aircraft Engine Emissions
Databank). The model then determines the quantities of these substances through the “Boeing Fuel Flow Method 2” 46.
Next-generation aircraft that are not officially captured by the BADA database are simulated by target mission
performance (i.e., fuel burn in particular) enhancements.
III. Reference air-traffic-growth scenario and future fleet inventory
A. Market forecasts considered
In order to derive air traffic growth rates for a future reference scenario, industry growth data forecast25 were used
up to the year 2035. From 2035 onwards, a constant growth rate was assumed.
B. Fleet inventory
To estimate the fuel- and emissions-reduction potential of the next-generation aircraft types under different
technology-improvement scenarios (i.e., by varying the fuel efficiency improvements associated to each next-
8
American Institute of Aeronautics and Astronauticsgeneration aircraft type), today’s air transport fleet was reduced to nine representative aircraft categories, in which
each one of the categories is represented by a typical aircraft type. The assignment was done on an ASK/ATK-share
basis for each category. The nine aircraft categories comprise two different types of freighters (mid- and long-range
freighters), four clusters for different twin-aisle long-range aircraft, and three single-aisle categories, of which two are
powered by a turbofan and one by a turboprop propulsion system.
IV. Aircraft fleet level results of technological and operational scenarios
Based on the results up to the year 2025 23, a baseline and three overall emission reduction scenarios -namely
Conservative, Ambitious and Radical- were calculated taking new aircraft programs (Case 1.1-1.3), aircraft production
ramp-ups (Case 2.1-2.3), increased aircraft productivities (Case 3.1-3.3), change of regional RPK growth rates (Case
4) and aircraft retrofit technologies (Case 5) into account. A full list of considered cases in each of the scenarios can
by found in Table 2. For the Baseline scenario, no new aircraft programs with reduced fuel burns are introduced after
2017 (see also Figure 1). Based on forecasted production rates for cluster 2 to 9 (see Annex 1), production rates after
year 202034 follow the growth rates from the industry forecast25 and seat loadfactors will linearly increase from 80.2%
in 201536 to 95% in 2050.
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
The Conservative scenario consists of shortfalls in fuel burn reductions compared to SRIA goals, status-quo
production ramp-ups and increase of aircraft productivity within six years.
The Ambitious scenario consists of shortfalls in fuel burn reductions compared to SRIA goals before 2035,
production ramp-ups and increase of aircraft productivity within three years as well as retrofit solutions for current in-
service aircraft fleet.
The Radical scenario consists of new aircraft programs meeting the SRIA goals until 2050, production ramp-ups
and increase of aircraft productivity within only one year, reduction of regional RPK growth rates to 50% assuming a
stronger shift from air to ground on a regional level, as well as retrofit solutions for current in-service aircraft fleet.
Besides the consolidated three scenarios, each case inside each scenario was consecutively calculated and a
summary of all simulations in each of the scenarios as well as considered cases are shown in Table 2.
Table 2. Summary of technological and operational cases for Conservative, Ambitious and Radical scenarios
Scenarios: Conservative Ambitious Radical
Cases: 1 2 3 4 1 2 3 4 5 1 2 3 4 5 6
Case 1.1: -43% fuel burn of all new aircraft with EIS between 2020 and 2035, -60% fuel burn of all new aircraft with EIS
between 2035 and 2050
x x x x x x
Case 1.2: -22% (~50% shortfall due to no new A/C programs) fuel burn of re-engined, re-winged A/C between 2020 and 2035,
-60% fuel burn of all new aircraft with EIS between 2035 and 2050
x x x x x
Case 1.3: -22% (~50% shortfall due to no new A/C programs) fuel burn of re-engined, re-winged A/C between 2020 and 2035,
-48% (~20% shortfall) fuel burn of all new aircraft with EIS between 2035 and 2050
x x x x
Case 2.1: New aircraft programs with ramp-up timelines of 6 years x x x x
Case 2.2: New aircraft programs with ramp-up timelines of 3 years x x x x x
Case 2.3: New aircraft programs with ramp-up timelines of 1 year x x x x x x
Case 3.1: Increase of average load factor to 95% until 2025 x x x x x x x x x x x x
Case 3.2.A: Increase of average number of installed seats by 10% from 2017 within 6 years x x
Case 3.2.B: Increase of average number of installed seats by 10% from 2017 within 3 years x x x
Case 3.2.C: Increase of average number of installed seats by 10% from 2017 within 1 year x x x x
Case 3.3.A: Increase of average aircraft utilization by 10% from 2017 within 6 years x
Case 3.3.B: Increase of average aircraft utilization by 10% from 2017 within 3 years x x
Case 3.3.C: Increase of average aircraft utilization by 10% from 2017 within 1 year x x x
Case 4: Reduction of regional RPK growth rates (e.g. inside EU, USA and Asia) of 50% x x
Case 5: Application of retrofit solution for in-fleet aircraft from 2008 until last retired A/C from initial fleet x x
9
American Institute of Aeronautics and Astronautics900
As shown in Figure 2, the introduction of new aircraft
programms with lower fuel burn (-22 % in 2020-2035 and 800
-48% in the timeframe 2035-2050) show a significant
700
reduction on fleet level fuel burn for the Conservative 1
scenario compared to the Baseline after 2035. With rising
Global Fuel burn (in Mt)
600
aircraft productivity by increasing loadfactors
500
(Conservative 2-4) and average number of installed seats
(Conservative 3-4) a further decrease of growth of fleet 400
level fuel consumption after the year 2020 can be
300
observed. These modelled improvements lead to a
decrease of fleet level fuel burns in the years 2024-2025. 200
After 2025, modelled aircraft productivity enhancements
100
reach their maximum, hence fleet level fuel burns start to
rise again. Aircraft utilisation increase (Conservative 4) 0
2000 2010 2020 2030 2040 2050
does not result in major fleet level fuel burn improvements
because the fleet model retirements are based on static Fuel Burn Baseline Fuel Burn Conservative 1 Fuel Burn Conservative 2
survival curves, hence the model does not consider shorter Fuel Burn Conservative 3 Fuel Burn Conservative 4
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
aircraft lifetimes due to higher utilisation. However, the Figure 2: Fleet-level fuel burn from 2008 to 2050 for
number of required aircraft is reduced by -10 %. A similar Baseline and Conservative 1-4 scenarios
impact of aircraft productivity enhancements could be
observed for the Ambitious and Radical scenarios. The
Conservative 1 and Conservative 2 scenarios resulted in
similar fleet level fuel burn values due to same target load
factors in 2050.
Comparing the Conservative 1-4 with the Baseline
scenarios, fleet level fuel burns in 2050 can be reduced by
-40 % (Conservative 1) up to -45 % (Conservative 4).
Comparing the 2050 results with 2008, fleet level fuel
burns will increase by a factor of 4.5 for the Baseline, 2.7
for Conservative 1 and 2.5 for Conservative 4 scenario.
Comparing cumulative fleet-level fuel burns from year
2008 to year 2050 (see Figure 3), the introduction of new
aircraft programs will lower cumulative fleet-level fuel
burn by -17 %. This reduction shows significantly the
slowing effect of market penetration of lower fuel burn
technologies and aircraft programs on global fleet level.
The increase of loadfactor further reduces cumulative fleet Figure 3: Cumulative fleet-level fuel burns from 2008
level fuel burns by additional -5 %, an increase of installed to 2050 of Conservative 1-4 relative to Baseline
seats further reduces cumulative fuel burns by another -2
%. As mentioned before, aircraft utilisations does not show
significant fuel burn reduction potential. In total
Conservative 4 delivers a -25 % lower cumulative fleet-
level fuel burn compared to the Baseline.
Comparing cumulative fleet-level fuel burns for the
Ambitious 1 to 5 (see Figure 4), the introduction of new
aircraft programs will lower cumulative fleet-level fuel
burn by -22 %. Comparing it with the Conservative 1, the
slowing effect of market penetration of lower fuel burn
technologies and aircraft programs on global fleet level
even with more ambitious production ramp-ups of only
three years until full production can be observed. The
increase of loadfactor further reduces cumulative fleet
level fuel burns by additional -6 %, an increase of installed
seats further reduces cumulative fuel burns by another -2
Figure 4: Cumulative fleet-level fuel burns from 2008
%. The application of retrofit solutions for in-fleet aircraft
to 2050 of Ambitious 1-5 relative to Baseline
from 2008 with a full market penetration until 2025 will
10
American Institute of Aeronautics and Astronauticsreduce the cumulative fleet-level fuel burns by another -3
%. In total, Ambitious 5 delivers a -31% lower cumulative
fleet-level fuel burn compared to the Baseline.
Finally comparing cumulative fleet-level fuel burns for
the Radical 1 to 6 (see Figure 5), following the SRIA fuel
burn reduction goals together with radical aircraft
production ramp-ups of one year lower cumulative fleet-
level fuel burn by -27 %. Similar to Conservative and
Ambitious scenarios, the slowing effect of market
penetration of lower fuel burn technologies and aircraft
programs on global fleet level even at radical production
ramp-ups limits the effectiveness of fleet-level fuel burns.
The increase of loadfactor further reduces cumulative
fleet level fuel burns by additional -6 %, an increase of
installed seats further reduces cumulative fuel burns by
another 1%. As mentioned before, aircraft utilisation
Figure 5: Cumulative fleet-level fuel burns from 2008
increase does not show additional fuel burn saving
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
to 2050 of Radical 1-6 relative to Baseline
potentials (Radical 4). Halving the RPK growth rates for
the North American, European and Asian region leads to a
further decrease of cumulative fleet-level fuel burns of another -6 %. The application of retrofit solutions for in-fleet
aircraft from 2008 with a full market penetration until 2025 will reduce the cumulative fleet-level fuel burn by another
-3 %. In total, Radical 6 delivers a -43 % lower cumulative fleet-level fuel burn compared to the Baseline.
Comparing the scenarios with the lowest fleet-level fuel burns like Conservative 4, Ambitious 5 and Radical 6 with
the Baseline as well as with the ATAG targets (as shown in Figure 6), it can be seen that even for the Radical 6
scenario a negative fleet-level fuel burn year-over-year change cannot be achieved. Only a carbon neutral-growth until
2050 can be almost achieved in case of the Radical 6 scenario. However, delivering new aircraft programs with an
average fuel burn reduction of -43 % covering all current market segments from regional turbo-prop to large long-
range aircraft until 2035 and -60 % fuel burn consumptions between 2035 and 2050, will greatly challenge the aviation
industry. Therefore, even with these technology improvements, significant operational improvements as well as
reduction of RPK growth rates will not fullfill the ATAG 2050 goals. Therefore, alternative fuels are required to limit
fleet-level fuel burn to meet the ATAG 2050 goals for the given RPK growth until year 2050.
1.000
900
800
700
Global Fuel burn (in Mt)
600
500
400
300
200
100
0
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
Baseline (No Action) Conservative 4 Ambitious 5 Radical 6 ATAG targets (schematic)
Figure 6: Fleet-level fuel burn of Baseline, Conservative 4, Ambitious 5, Radical 6 and ATAG targets from year
2008 to year 2050.
11
American Institute of Aeronautics and AstronauticsV. Conclusion and Outlook
Simulating the impact of new aircraft programs with lower fuel consumptions together with aircraft production
ramp-ups, increased aircraft productivities, change of regional RPK growth rates and aircraft retrofit technologies led
to fifteen different scenarios. New aircraft technologies together with up to radical ramp-up timelines might lower
fleet-level fuel burn until year 2050 between -17 % to -27 %. Increasing aircraft productivity by increasing loadfactors,
installed seats and increased aircraft utilisation further reduce fleet-level fuel burn until year 2050 of -7 % to -8 %.
The application of retrofit solutions for in-fleet aircraft can reduce the fleet-level fuel burn until year 2050 of around
-3 %. Halving regional RPK growth rates might lead to fleet-level fuel burn reductions of around -6 % until year 2050.
Comparing the cumulative fleet-level fuel burns for the Baseline, Conservative, Ambitious, Radical with the
ATAG goals from 2008 to 2050, none of these fifteen scenarios is able to fulfil the ATAG long term goal of a -50 %
reduction global emission reduction compared to the year 2005.
The emission of the Baseline scenario exceeds the ATAG goal in 2050 by a factor of 11.7. The Conservative 4
scenario exceeds the goal by a factor of 6.4 and 5.1 for Ambitious 5 scenario. Even for the most stringent scenario
(Radical 6), fleet-level fuel burn exceeds the ATAG goals by a factor of 3.8.
Comparing the cumulative fleet-level fuel burn results of the scenarios with the ATAG goals, in the Baseline
scenarios, 2.2 times more fuel is consumed. For the Conservative 4 scenario, the factor is 1.6. The Ambitious 5 scenario
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
delivers 1.5 times higher cumulative fuel burn values. Even the stringent Radical 6 scenario exceeds the emission by
a factor of 1.3 compared to the ATAG goals. Therefore, even more radical aircraft technologies and morphologies
with higher CO2 emissions reduction potential with EIS well before 2050, lower RPK growth rates or renewable,
“drop-in” fuels, offering substantially smaller CO2 footprints compared to conventional jet fuel have to be considered
to fill this gap.
References
1ICAO data, Facts and Figures, URL: http://www.icao.int/sustainability/Pages/FactsFigures_WorldEconomyData.aspx, last cited:
26.08.2016
2Airbus, 2012. Global Market Forecast 2012-2031: Navigating the Future.
3Airport Council International (ACI), 2009. Global Traffic Forecast 2008-2027 – Edition 2009
4Boeing, 2012. Current Market Outlook 2012-2031.
5DKMA, 2013. Traffic Forecast Advisory Services – 20 Year Outlook
6Embraer, 2012. Market Outlook 2012-2031.
7International Civil Aviation Organization (ICAO), 2010. Aviation Outlook - Environmental Report 2010
8International Civil Aviation Organization (ICAO), 2007. Outlook for Air Transport to the Year 2025.
9Marketing Group of Japan Aircraft, 2011. Worldwide Market Forecast For Commercial Air Transport 2011-2030
10Rolls Royce, 2009. Market Outlook 2009 – Forecast 2009-2028
11Teyssier, N. (ICAO), 2012. ACI Airport Statistics and Forecasting Workshop – Aviation Statistics & Data: A Vital Tool for the
Decision Making Process. Presentation.
12Teyssier, N. (ICAO), 2012. 37th FAA Aviation Forecast Conference – Global Air Transport Outlook. Presentation.
13HSBC Global Research, 2012, The World in 2050- From the Top 30 to the Top 100
14ICAO, Environmental report 2013. Aviation and climate change, International Civil Aviation Organization, Montreal, Canada,
2013.
15IATA, A global approach to reducing aviation emissions. First stop: Carbon-neutral growth from 2020, International Air
Transport Association, Montreal, Canada, 2009.
16ATAG, The right flightpath to reduce aviation emissions, Air Transport Action Group, Durban, South Africa, 2011.
17European Union, Flightpath 2050 - Europe's vision for aviation.
18NASA Environmentally Responsible Aviation, “N+2 Advanced Vehicle Concepts NASA Research Announcement (NRA)”,
2010
19
Advisory Council for Aeronautical Research in Europe (ACARE), “European Aeronautics: A Vision for 2020”, January 2001
20Muller, R. (ASD AeroSpace and Defence Industries Association of Europe), “ACARE Goals (AGAPE) Progress Evaluation”,
Project Final Report Publishable Summary, Support Action Funding Scheme, Proposal No. 205768, European Commission
Directorate General for Research and Innovation, June 2010
21Aviation Week, Operators Reporting Positive 787 Fuel-Burn Results, URL: http://aviationweek.com/awin/operators-reporting
positive-787-fuel-burn-results, last cited: 26.08.2016
22Airbus A350 XWB Family Website URL: http://www.airbus.com/aircraftfamilies/passengeraircraft/a350xwbfamily/, last cited:
26.08.2016
23Randt N.P., Jessberger C., Ploetner K.O., Estimating the Fuel Saving Potential of Commercial Aircraft in Future Fleet-
Development Scenarios; AIAA Aviation 2015 Conference, Dallas, USA, 2015
24MTU Aero Engines, Product Leaflet PW1000G
25Boeing, Boeing Current Market Outlook 2015-2034
12
American Institute of Aeronautics and Astronautics26Dray L. M., Evans A., Schäfer A., 2010 The Impact of Economic Emissions Mitigation Measures on Global Aircraft Emissions,
last cited: 15.07. 2016, URL: http://aimproject.aero/Documents/ATIO2010Dray.pdf.
27Owen B, Lee D.S., Lim L. 2010.Flying into the Future: Aviation Emissions Scenarios to 2050. Environmental science &
technology 2010;44:2255–60.
28ICAO. ICAO Environmental Report 2016. Aviation and climate change, International Civil Aviation Organization, Montreal,
Canada, 2016.
29Hassan M., Payan A., Pfaender H.., Garcia E., Schutte J., Mavris D.. 2015. Framework Development for Performance Evaluation
of the Future National Airspace System, URL:
https://www.researchgate.net/publication/280114298_Framework_Development_for_Performance_Evaluation_of_the_Futur
e_National_Airspace_System, last cited: 12.09.2016
30Schilling T., Rötger., T, Wicke, K. 2016. AIRCAT Assessment of the Impact of Radical Climate-Friendly Aviation
Technologies.Hamburg; URL: http://elib.dlr.de/106658/1/2016_GreenerAviation_Paper_AIRCAT_20160906.pdf, last cited:
03.02.2017
31IATA 2013. IATA Technology Roadmap, URL: https://www.iata.org/whatwedo/environment/Documents/technology-roadmap-
2013.pdf, last cited: 24.04.2015
32Flightglobal.com, Flying to the future, https://www.flightglobal.com/sponsored/airbus/airframes/, last cited: 20.04.2017
33Heinemann P., Panagiotou P., Vratny P, Kaiser S., Hornung M., Yakinthos K.. Advanced Tube and Wing Aircraft for Year 2050
Timeframe, 55th AIAA Aerospace Sciences Meeting, AIAA SciTech Forum, (AIAA 2017-1390),
http://dx.doi.org/10.2514/6.2017-1390
Downloaded by Kay Ploetner on June 13, 2017 | http://arc.aiaa.org | DOI: 10.2514/6.2017-3771
34Leeham, Airbus/Boeing production rates forecast through 2020, URL: https://leehamnews.com/2015/02/03/airbusboeing-
production-rates-forecast-through-2020/ last cited: 20.04.2017
35Thomson, R., What the world's aerospace industry leaders are thinking: Implications for the supply chain, Midlands Aerospace
Alliance Annual Conference, Derby, United Kingdom, 2014
36IATA, Fact Sheet Industry Statistics, http://www.iata.org/pressroom/facts_figures/fact_sheets/Documents/fact-sheet-industry-
facts.pdf, last cited: 20.04.2017
Annex 1:
Table 2: Summary of monthly production rates for cluster 2 to 9 from 2008 until 2020 34
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
C2: Long-range heavy (TA) 1 1 2 2 4 3 3 4 4 4 4 3 3
C3: Mid-range freighter (n/a) 2 2 2 2 2 2 2 2 2 2 2 2 0
C4:Jet commuter (SA) 18 15 12 11 10 10 8 10 13 21 30 30 30
C5: Long-range freighter (n/a) 0 0 0 1 1 2 1 1 1 1 1 1 1
C6: Turboprop commuter (SA) 9 9 9 8 8 9 7 7 8 9 10 10 10
C7: Mid-range (TA) 7 7 8 9 14 16 19 21 20 20 25 23 23
C8: Long-range (TA) 7 9 7 7 7 9 9 12 15 16 17 18 22
C9: Short-medium range (SA) 57 65 65 67 73 78 82 84 93 93 106 116 126
13
American Institute of Aeronautics and AstronauticsYou can also read
